Emotion-Based Matching of Music to Places

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Abstract

Music and places can both trigger emotional responses in people. This chapter presents a technical approach that exploits the congruence of emotions raised by music and places to identify music tracks that match a place of interest (POI). Such technique can be used in location-aware music recommendation services. For instance, a mobile city guide may play music related to the place visited by a tourist, or an in-car navigation system may adapt music to places the car is passing by. We address the problem of matching music to places by employing a controlled vocabulary of emotion labels. We hypothesize that the commonality of these emotions could provide, among other approaches, the base for establishing a degree of match between a place and a music track, i.e., finding music that “feels right” for the place. Through a series of user studies we show the correctness of our hypothesis. We compare the proposed emotion-based matching approach with a personalized approach where the music track is matched to the music preferences of the user, and to a knowledge-based approach which matches music to places based on metadata (e.g., matching music that was composed during the same period that the place of interest was built in). We show that when evaluating the goodness of fit between places and music, personalization is not sufficient and that the users perceive the emotion-based music suggestions as better fitting the places. The results also suggest that emotion-based and knowledge-based techniques can be combined to complement each other.